| 引用本文: | 刘福全,杜 崇,韩 旭,等.基于3S技术的大庆地区土壤盐渍化时空变化分析[J].灌溉排水学报,2022,41(5):132-138. |
| LIU Fuquan,DU Chong,HAN Xu,et al.基于3S技术的大庆地区土壤盐渍化时空变化分析[J].灌溉排水学报,2022,41(5):132-138. |
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| 摘要: |
| 【目的】监测大庆地区土壤盐渍化的时空变化规律。【方法】基于不同深度土壤含盐量实测数据结合Landsat系列遥感影像反射率进行相关性分析，筛选出敏感波段，以多元逐步回归分析的方法构建土壤盐渍化反演模型，用ArcGIS绘制盐碱化等级分布图，分析2001—2021年土壤盐渍化时空变化特征。【结果】①表层（0~10 cm）土壤含盐量与反射率相关性更强，将反射率经过数学变换之后相关性也会有所提升。②B1波段对数、B7波段和B7波段的指数构建的反演模型精度和稳定性都表现良好，R2=0.842，RMSE=0.290，可以用作研究区的反演模型。③2001—2021年研究区轻度盐碱化、中度盐碱化和盐土面积先增加后减少，重度盐碱化面积呈先减再增后减的趋势，到2021年为止研究区盐碱化总面积为102 262 hm2。【结论】2001—2021年大庆地区盐碱化面积总体来说先增加后减少，特别是大庆市区盐碱化面积减少幅度最大，在今后的工作中应该重点监测盐渍土面积较多的杜蒙和林甸2个县，确保盐碱化程度不再继续加重。 |
| 关键词: 大庆地区；土壤含盐量；遥感；时空变化 |
| DOI：10.13522/j.cnki.ggps.2021494 |
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| Spatiotemporal Variation in Soil Salinization in Daqing Calculated Using the 3S Technology |
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LIU Fuquan, DU Chong, HAN Xu, LI Rui, HU Zihao, GUO Jiatong
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1. College of Water Resources and Electric Power, Harbin 150080, China;
2. Liaoning Shifosi Reservoir Administration Co. LTD, Shenyang 110166, China
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| Abstract: |
| 【Objective】Soil salinization is an abiotic stress affecting crop production in most countries across the world. Understanding spatiotemporal dynamics of soil salt at catchment and regional scales is crucial to improving soil management but challenging because of its spatial heterogeneity over different scales. The purpose of this paper is to present a new method to estimate soil salinity distribution at regional scale.【Method】The proposed method is based on satellite imagery. Using salt contents measured at different soil depths and the reflectance of Landsat remote sensing images, an inversion model linking soil salinization with the most sensitive imagery-bands was constructed by multiple stepwise regression analysis methods. The spatial distribution of soil salinization was calculated using the Arcgis. We applied the model to soil salinization data measured from 2001 to 2021 in Daqing, Heilongjiang province. 【Result】①Correlation between soil salt content and the reflectance was better for the surface soil layer (0~10 cm) than for the subsoil; its accuracy can be further improved by mathematical transformations of the reflectance. ②The inversion model constructed by the logarithm of B1 band, the index of B7 band and B7 bands was accurate and stable with R2=0.842 and RMSE=0.290. ③From 2001 to 2021, the areas with mild, moderate salinized soils increased first followed by a decline, while the areas with severe salinization decreased first, following by an increase before falling again. By 2021, the total salinized areas in the studied region were 102 262 hm2. 【Conclusion】 From 2001 to 2021, the salinized areas in Daqing increased first and then declined. In particular, salinization areas in the urban areas decreased fastest. We recommended that soil salinization monitoring should focus on the salinity-laten region at Dumeng and Lindian counties to control their increase. |
| Key words: Daqing; soil salinity; remote sensing; spatiotemporal variation |
